| Abstract Scope |
Wire Arc Additive Manufacturing (WAAM) is an emerging advanced manufacturing technology. In 2024, LeTourneau University acquired two new Yaskawa welding robots to strengthen welding engineering education and training. These robotic platforms provided an opportunity to establish WAAM capabilities within the welding engineering program. To achieve this goal, a senior design project was launched during the 2025–2026 academic year.**
The first phase of the project investigated the feasibility of employing three Gas Metal Arc Welding (GMAW) metal transfer modes—Cold Metal Transfer (CMT), Regulated Metal Deposition (RMD), and Surface Tension Transfer (STT)—for WAAM of duplex stainless steel (DSS) 2209. Vertical wall specimens were fabricated and evaluated through visual inspection, metallography, hardness testing, tensile testing, and impact testing. Among the three processes, CMT yielded the highest-quality deposits, exhibiting excellent surface finish and no observable spatter or internal defects. RMD and STT produced deposits with varying levels of spatter but showed no lack of fusion, porosity, or cracking. All walls displayed similar hardness distributions and ferrite numbers near 40. Impact toughness averaged approximately 100 ft-lbs for CMT wall and 82 ft-lbs for both RMD wall and STT wall, while ultimate tensile strengths exceeded 105 ksi for all specimens. No significant anisotropy was observed in either toughness or tensile properties. **
The second phase focused on developing an integrated WAAM software toolchain that combines Fused Deposition Modeling (FDM)-inspired slicing strategies with industrial robotic welding. A custom WAAM slicer was developed and the RoboDK post-processor was used to address limitations of conventional FDM software and provide enhanced control over heat input, bead geometry, seam placement, and contact-tip-to-work distance. Validation through fabrication of increasingly complex geometries demonstrated improved process stability, reduced programming effort, and repeatable deposition performance. The resulting workflow establishes a practical and scalable foundation for future adaptive and multi-axis WAAM systems. |